Referenced statement

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Semantic MediaWiki statement with untested claim or fact
Semantic MediaWiki statement containing a factual claim
Example implementation

Statements recorded with Semantic MediaWiki mostly contain untested claims which in general is being interpret as an "incomplete claim for which evidence is yet unavailable"

For example, the statement "Berlin has a population of 3 500 000" is untested in context of a missing reference or axiomatic declaration, yet in spite of lacking evidence the claim is expected to be truelogical.axiom (under the open-world assumption).

Some usersgh:smw:985 and for some situations, relying on untested claims can be challenging therefore SMW 2.5 introduced a new Referencegh:smw:1812 type with which an untested claim can be transformed into a factual claim by recording provenance metadatagh:smw:1808Ram:2009:NPS:2889875.2889882Simmhan:2005:SDP:1084805.1084812 (as to when, how, by whom a claim was made) and hereby allows to state tangible or convergent

Semantic Cite vs. Reference type

A statement created by Semantic Cite (also known as citation resource) and that by the Reference type are fundamentally different in that, references (referring to the provenance metadata) are an extension of a value statement and inherently bound to a specific value assignment while Semantic Cite's resources are "loose" references that can be freely attached to any text or link without correlation to a specific claim or value annotation.


|citation text=Fact, Opinion, False Claim, or Untested Claim? describes as "Untested claim: Vague, ambiguous, or incomplete claim OR factual claim for which evidence is yet unavailable."


|citation text=As a logical axiom "everything can be true unless proven otherwise", see The Open World Assumption


|citation text=


|citation text=


|citation text=


author = {Ram, Sudha and Liu, Jun},
title = {A New Perspective on Semantics of Data Provenance},
booktitle = {Proceedings of the First International Conference on Semantic Web in Provenance Management - Volume 526},
series = {SWPM'09},
year = {2009},
location = {Washington DC},
pages = {35--40},
numpages = {6},
url = {},
acmid = {2889882},
publisher = {},
address = {Aachen, Germany, Germany},


|keywords=Data Provenance,ontological model,W7 model,provenance semantics|+sep=,
|abstract=Data Provenance refers to the "origin", "lineage", and "source" of data. In this work, we examine provenance from a semantics perspective and present the W7 model, an ontological model of data provenance. In the W7 model, provenance is conceptualized as a combination of seven interconnected elements including "what", "when", "where", "how", "who", "which" and "why". Each of these components may be used to track events that affect data during its lifetime. The W7 model is general and extensible enough to capture provenance semantics for data in different domains. Using the example of the Wikipedia, we illustrate how the W7 model can capture domain or application specific provenance.


author = {Simmhan, Yogesh L. and Plale, Beth and Gannon, Dennis},
title = {A Survey of Data Provenance in e-Science},
journal = {SIGMOD Rec.},
issue_date = {September 2005},
volume = {34},
number = {3},
month = sep,
year = {2005},
issn = {0163-5808},
pages = {31--36},
numpages = {6},
url = {},
doi = {10.1145/1084805.1084812},
acmid = {1084812},
publisher = {ACM},
address = {New York, NY, USA},


|keywords=Data management,Data Provenance,scientific workflow|+sep=,
|abstract=Data management is growing in complexity as large-scale applications take advantage of the loosely coupled resources brought together by grid middleware and by abundant storage capacity. Metadata describing the data products used in and generated by these applications is essential to disambiguate the data and enable reuse. Data provenance, one kind of metadata, pertains to the derivation history of a data product starting from its original sources.In this paper we create a taxonomy of data provenance characteristics and apply it to current research efforts in e-science, focusing primarily on scientific workflow approaches. The main aspect of our taxonomy categorizes provenance systems based on why they record provenance, what they describe, how they represent and store provenance, and ways to disseminate it. The survey culminates with an identification of open research problems in the field.